Mercurial > repos > bgruening > sklearn_label_encoder
view test-data/get_params03.tabular @ 9:5e1581dfb419 draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5eca9041ce0154eded5aec07195502d5eb3cdd4f
author | bgruening |
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date | Fri, 03 Nov 2023 22:54:44 +0000 |
parents | 3b6ee54eb7e2 |
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Parameter Value * memory memory: None * steps "steps: [('robustscaler', RobustScaler(copy=True, quantile_range=(25.0, 75.0), with_centering=True, with_scaling=True)), ('xgbclassifier', XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1, colsample_bytree=1, gamma=0, learning_rate=0.1, max_delta_step=0, max_depth=3, min_child_weight=1, missing=nan, n_estimators=100, n_jobs=1, nthread=None, objective='binary:logistic', random_state=0, reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None, silent=True, subsample=1))]" @ robustscaler "robustscaler: RobustScaler(copy=True, quantile_range=(25.0, 75.0), with_centering=True, with_scaling=True)" @ xgbclassifier "xgbclassifier: XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1, colsample_bytree=1, gamma=0, learning_rate=0.1, max_delta_step=0, max_depth=3, min_child_weight=1, missing=nan, n_estimators=100, n_jobs=1, nthread=None, objective='binary:logistic', random_state=0, reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None, silent=True, subsample=1)" @ robustscaler__copy robustscaler__copy: True @ robustscaler__quantile_range robustscaler__quantile_range: (25.0, 75.0) @ robustscaler__with_centering robustscaler__with_centering: True @ robustscaler__with_scaling robustscaler__with_scaling: True @ xgbclassifier__base_score xgbclassifier__base_score: 0.5 @ xgbclassifier__booster xgbclassifier__booster: 'gbtree' @ xgbclassifier__colsample_bylevel xgbclassifier__colsample_bylevel: 1 @ xgbclassifier__colsample_bytree xgbclassifier__colsample_bytree: 1 @ xgbclassifier__gamma xgbclassifier__gamma: 0 @ xgbclassifier__learning_rate xgbclassifier__learning_rate: 0.1 @ xgbclassifier__max_delta_step xgbclassifier__max_delta_step: 0 @ xgbclassifier__max_depth xgbclassifier__max_depth: 3 @ xgbclassifier__min_child_weight xgbclassifier__min_child_weight: 1 @ xgbclassifier__missing xgbclassifier__missing: nan @ xgbclassifier__n_estimators xgbclassifier__n_estimators: 100 * xgbclassifier__n_jobs xgbclassifier__n_jobs: 1 * xgbclassifier__nthread xgbclassifier__nthread: None @ xgbclassifier__objective xgbclassifier__objective: 'binary:logistic' @ xgbclassifier__random_state xgbclassifier__random_state: 0 @ xgbclassifier__reg_alpha xgbclassifier__reg_alpha: 0 @ xgbclassifier__reg_lambda xgbclassifier__reg_lambda: 1 @ xgbclassifier__scale_pos_weight xgbclassifier__scale_pos_weight: 1 @ xgbclassifier__seed xgbclassifier__seed: None @ xgbclassifier__silent xgbclassifier__silent: True @ xgbclassifier__subsample xgbclassifier__subsample: 1 Note: @, searchable params in searchcv too.